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At least 1,477 records · Page 82

Low-perigee aerodynamic heating during orbital flight of an atmosphere Explorer

An extensive, low-perigee orbital aerodynamic heating study was undertaken in support of the Atmosphere Explorer-C Temperature Alarm. State of the art of low-density, high-speed flows, some models of the earth's atmosphere, external flow-field definition, thermodynamic and transport properties of atmospheric gases, the accommodation coefficient orbital thermal environment, and correlation of theory and measurements are discussed. Aerodynamic heating rates are determined for eight selected orbits by means of a reduced, analytical model verified by both ground test and flight data. These heating rates are compared with classical free-molecule and first-order collision regime values.

Caruso, P. S., Jr.↗

Theoretical and empirical low perigee aerodynamic heating during orbital flight of an atmosphere explorer

This document presents the results of an extensive, low perigee, orbital aerodynamic heating study undertaken in support of the Atmosphere Explorer-C Temperature Alarm. Based upon in-flight orbital temperature data from the Temperature Alarm tungsten resistance wire thermometer, aerodynamic heating rates have been determined for eight selected orbits by means of a reduced thermal analytical model verified by both ground test and flight data. These heating rates are compared with the classical free molecular and first order collision regime values. It has been concluded that, for engineering purposes, the aerodynamic heating rate of atmospheric gases at perigee altitudes between 170 and 135 km on pure tungsten wire is 30 to 60% of the value set by the classical free molecular limit. Relative to the more usual orbital thermal input attributable to direct solar radiation, the aerodynamic heating rate at the lowest altitude attempted with the spacecraft despun (135 km) is the equivalent of about 1.2 solar constants incident on a tungsten wire with a solar absorptivity of 0.85.

Caruso, P. S., Jr.↗

Aircraft model prototypes which have specified handling-quality time histories

Several techniques for obtaining linear constant-coefficient airplane models from specified handling-quality time histories are discussed. The pseudodata method solves the basic problem, yields specified eigenvalues, and accommodates state-variable transfer-function zero suppression. The algebraic equations to be solved are bilinear, at worst. The disadvantages are reduced generality and no assurance that the resulting model will be airplane like in detail. The method is fully illustrated for a fourth-order stability-axis small motion model with three lateral handling quality time histories specified. The FORTRAN program which obtains and verifies the model is included and fully documented.

Johnson, S. H.↗

Evaluation and reduction of errors induced by the Guyan transformation

The Guyan reduction refers to a method used to reduce the number of degrees of freedom in a structural model for dynamic analysis. Experience shows that, if the method is properly employed, then this reduction method does in fact provide a "reasonably" accurate approximation of the dynamic characteristics of the unreduced model. A method that provides an accurate estimate of the error in each mode of the reduced eigenvalue problem and, in addition, gives first order correction terms that greatly improve the accuracy of the eigenvectors and eigenvalues is presented. The method is demonstrated by standard COSMIC NASTRAN DAMP alters to rigid format 3, real normal mode analysis. Comparative computer time of modal extraction versus error analysis is discussed for the VAX-11/780 version of COSMIC NASTRAN.

Fox, G. L.↗

Adding dynamic rules to self-organizing fuzzy systems

This paper develops a Dynamic Self-Organizing Fuzzy System (DSOFS) capable of adding, removing, and/or adapting the fuzzy rules and the fuzzy reference sets. The DSOFS background consists of a self-organizing neural structure with neuron relocation features which will develop a map of the input-output behavior. The relocation algorithm extends the topological ordering concept. Fuzzy rules (neurons) are dynamically added or released while the neural structure learns the pattern. The DSOFS advantages are the automatic synthesis and the possibility of parallel implementation. A high adaptation speed and a reduced number of neurons is needed in order to keep errors under some limits. The computer simulation results are presented in a nonlinear systems modelling application.

Buhusi, Catalin V.↗

Linear quadratic Gaussian and feedforward controllers for the DSS-13 antenna

The controller development and the tracking performance evaluation for the DSS-13 antenna are presented. A trajectory preprocessor, linear quadratic Gaussian (LQG) controller, feedforward controller, and their combination were designed, built, analyzed, and tested. The antenna exhibits nonlinear behavior when the input to the antenna and/or the derivative of this input exceeds the imposed limits; for slewing and acquisition commands, these limits are typically violated. A trajectory preprocessor was designed to ensure that the antenna behaves linearly, just to prevent nonlinear limit cycling. The estimator model for the LQG controller was identified from the data obtained from the field test. Based on an LQG balanced representation, a reduced-order LQG controller was obtained. The feedforward controller and the combination of the LQG and feedforward controller were also investigated. The performance of the controllers was evaluated with the tracking errors (due to following a trajectory) and the disturbance errors (due to the disturbances acting on the antenna). The LQG controller has good disturbance rejection properties and satisfactory tracking errors. The feedforward controller has small tracking errors but poor disturbance rejection properties. The combined LQG and feedforward controller exhibits small tracking errors as well as good disturbance rejection properties. However, the cost for this performance is the complexity of the controller.

Gawronski, W. K.↗

Structural Analysis of Composite Test panels

An analytical study was conducted for a 1/4 scale model skin-stringer compression panel using STructural Analysis of General Shells (STAGS) code for finite element analysis. This was a study to investigate scaling methods for composite structures using reduced ply thicknesses for 1/2 and 1/4 scale models. A computer model for a curved panel in a pressure-box was also constructed in order to simulate test conditions in the pressure box test machine. The pressure box is a test facility at NASA Langley Research Center used to simulate flight conditions in fuselage panels. This model will be used to investigate modifications to the pressure-box for curved panels with different radii.

Berhan, Sean↗

Frustration- and doping-induced magnetism in a Fermi–Hubbard simulator

Geometrical frustration in strongly correlated systems can give rise to a plethora of novel ordered states and intriguing magnetic phases, such as quantum spin liquids. Promising candidate materials for such phases can be described by the Hubbard model on an anisotropic triangular lattice, a paradigmatic model capturing the interplay between strong correlations and magnetic frustration. However, the fate of frustrated magnetism in the presence of itinerant dopants remains unclear, as well as its connection to the doped phases of the square Hubbard model. Here we investigate the local spin order of a Hubbard model with controllable frustration and doping, using ultracold fermions in anisotropic optical lattices continuously tunable from a square to a triangular geometry. At half-filling and strong interactions U/t ≈ 9, we observe at the single-site level how frustration reduces the range of magnetic correlations and drives a transition from a collinear Néel antiferromagnet to a short-range correlated 120° spiral phase. Away from half-filling, the triangular limit shows enhanced antiferromagnetic correlations on the hole-doped side and a reversal to ferromagnetic correlations at particle dopings above 20%, hinting at the role of kinetic magnetism in frustrated systems. Furthermore, this work paves the way towards exploring possible chiral ordered or superconducting phases in triangular lattices and realizing t–t' square lattice Hubbard models that may be essential to describe superconductivity in cuprate materials.

74 ATOMIC AND MOLECULAR PHYSICS↗

Analytical-HZETRN Model for Rapid Assessment of Active Magnetic Radiation Shielding

The use of active radiation shielding designs has the potential to reduce the radiation exposure received by astronauts on deep-space missions at a significantly lower mass penalty than designs utilizing only passive shielding. Unfortunately, the determination of the radiation exposure inside these shielded environments often involves lengthy and computationally intensive Monte Carlo analysis. In order to evaluate the large trade space of design parameters associated with a magnetic radiation shield design, an analytical model was developed for the determination of flux inside a solenoid magnetic field due to the Galactic Cosmic Radiation (GCR) radiation environment. This analytical model was then coupled with NASA's radiation transport code, HZETRN, to account for the effects of passive/structural shielding mass. The resulting model can rapidly obtain results for a given configuration and can therefore be used to analyze an entire trade space of potential variables in less time than is required for even a single Monte Carlo run. Analyzing this trade space for a solenoid magnetic shield design indicates that active shield bending powers greater than 15 Tm and passive/structural shielding thicknesses greater than 40 g/cm2 have a limited impact on reducing dose equivalent values. Also, it is shown that higher magnetic field strengths are more effective than thicker magnetic fields at reducing dose equivalent.

Washburn, S. A.↗

Task II: Three-dimensional Rotating Stall Inception and Effects of Rotating Tip Clearance Asymmetry in Axial Compressors

The effects of two types of flow non-uniformity on stall inception behavior were assessed with linearized stability analyses of two compressor flow models. Response to rotating tip clearance asymmetries induced by a whirling rotor shaft or rotor height variations were investigated with a two-dimensional flow model. A 3-D compressor model was also developed to study the stability of both full-span and part-span rotating stall modes in annular geometries with radial flow variations. The studies focussed on (1) understanding what compressor designs were sensitive to these types of circumferential and spanwise flow non-uniformities, and (2) situations where 2-D stability theories were inadequate because of 3-D flow effects. Rotating tip clearance non-uniformity caused the greatest performance loss for shafts whirling at the rotating stall frequency. A whirling shaft displacement of 1 percent chord caused the stalling mass flow to rise by as much as 10 percent and the peak pressure rise to decrease by 6 percent. These changes were an order of magnitude larger than for equivalent-sized stationary or rotor-locked clearance asymmetries. Spanwise flow non-uniformity always destabilized the compressor, so that 2-D models over-predicted that stall margin compared to 3-D theory. The difference increased for compressors with larger spanwise variations of characteristic slope and reduced characteristic curvature near the peak. Differences between 2-D and 3-D stall point predictions were generally unacceptable (2 - 4 percent of flow coefficient) for single-stage configurations, but were less than 1 percent for multistage compressors. 2-D analyses predicted the wrong stall mode for specific cases of radial inlet flow distortion, mismatching and annulus area contraction, where higher-order radial modes led to stall. The stability behavior of flows with circumferential or radial non-uniformity was unified through a single stability criterion. The stall point for both cases was set by the integral around the annulus of the pressure rise characteristic slope, weighted by the amplitude of the mode shape. For the case of steady circumferential variations, this criterion reduced to the integrated mean slope (IMS) condition associated with steady inlet distortions. The rotating tip clearance asymmetry model was also used to demonstrate the feasibility of actively controlling the shaft position to suppress rotating stall. In axisymmetric mean flow, this method only stabilized the first harmonic mode, increasing the operating range until surge or higher harmonic modes became unstable.

Suder, Kenneth↗

Report on the Use and Function of the Integrated Operations Capability Analysis Platform (ICAP) and the LWRS Innovation Portal (IP)

The commercial nuclear power industry has achieved excellent safety and reliability performance but is struggling to survive in an electricity market that is increasingly dominated by subsidized renewables and cheap natural gas. These challenges have forced utilities to explore previously uncharted avenues to drastically reduce the operations and maintenance costs of their plants which are the primary drivers of the total cost to produce electricity. The petrochemical industry faced similar challenges some years ago as the costs of extraction and processing were rising while their reservoirs were being depleted along with a drop-in commodity prices that resulted in unsustainable operations. In this challenging climate, they developed a business model called Integrated Operations (IO) that sought to utilize technology to enable news ways of working through the integration of people, technology, process and governance changes. The Light Water Reactor Sustainability (LWRS) program, working with IFE have developed an operating model via transferable learnings from the North Sea O&G industry. This framework is termed “Integrated Operations for Nuclear” (ION). ION is a transformation model that integrates the benefits and features of four principal factors: People, Technology, Process and Governance. The purpose of this report is to describe how to generate an ION business process analysis and utilize this information to reduce O&M costs. In order to make this job easier, DOE LWRS has created a suite of tools that will allow a person who is involved in a transformation effort at their company to build a solid documented business case for embarking on a major transformation effort. These tools, the Integrated Operations Capability Analysis Model (ICAP) and the LWRS Innovation Portal (IP) are described herein with instructions on their use. Instructions on how the interface with the EPRI Business Case Analysis Method (BCAM) are also provided.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Reinforcement learning based automated history matching for improved hydrocarbon production forecast

History matching aims to find a numerical reservoir model that can be used to predict the reservoir performance. An engineer and model calibration (data inversion) method are required to adjust various parameters/properties of the numerical model in order to match the reservoir production history. In this study, we develop deep neural networks within the reinforcement learning framework to achieve automated history matching that will reduce engineers’ efforts, human bias, automatically and intelligently explore the parameter space, and remove the need of large set of labeled training data. To that end, a fast-marching-based reservoir simulator is encapsulated as an environment for the proposed reinforcement learning. The deep neural-network-based learning agent interacts with the reservoir simulator within reinforcement learning framework to achieve the automated history matching. Reinforcement learning techniques, such as discrete Deep Q Network and continuous Deep Deterministic Policy Gradients, are used toth, used to train the learning agents. The continuous actions enable the Deep Deterministic Policy Gradients to explore more states at each iteration in a a learning episode; consequently, a better history matching is achieved using this algorithm as compared to Deep Q Network. For simplified dual-target composite reservoir models, the best history-matching performances of the discrete and continuous learning methods in terms of normalized root mean square errors are 0.0447 and 0.0038, respectively. Furthermore, our study shows that continuous action space achieved by the deep deterministic policy gradient drastically outperforms deep Q network.

42 ENGINEERING↗

Comparison Between THOR Anthropomorphic Test Device and THOR Finite Element Model

Extended time spent in reduced gravity can cause physiologic deconditioning of astronauts, reducing their ability to sustain excessive forces during dynamic phases of spaceflight such as landing. To make certain that the crew is safe during these phases, NASA must take caution when determining what types of landings are acceptable based on the accelerations applied to the astronaut. In order to test acceptable landings, various trials have been run accelerating humans, cadavers, and Anthropomorphic Test Devices (ATDs), or crash test dummies, at different acceleration and velocity rates on a sled testing platform. Using these tests, risks of injury will be created and metrics will be developed for the likelihood of injuries due to the acceleration. A finite element model (FEM) of the Test Device for Human Occupant Restraint (THOR) ATD has been developed that can simulate these test trials and others (Putnam, 2014), reducing the need for human and ATD testing. Additionally, this will give researchers a more effective way to test the accelerations and orientations encountered during spaceflight landings during design of new space vehicles for crewed missions. However, the FEM has not been proven and must be validated by comparing the forces, accelerations, and other measurements of all parts of the body between the physical tests already completed and computer simulated trials. The purpose of my research was to validate the FEM for the ATD using previously run trials with the physical THOR ATD.

Moore, Erik↗

Opposite Responses of the Dry and Moist Eddy Heat Transport Into the Arctic in the PAMIP Experiments

Given uncertainty in the processes involved in polar amplification, elucidating the role of poleward heat and moisture transport is crucial. The Polar Amplification Model Intercomparison Project (PAMIP) permits robust separation of the effects of sea ice loss from sea surface warming under climate change. We utilize a moist isentropic circulation framework that accounts for moisture transport, condensation, and eddy transport, in order to analyze the circulation connecting the mid-latitudes and the Arctic. In PAMIP's atmospheric general circulation model experiments, prescribed sea ice loss reduces poleward heat transport (PHT) by warming the returning moist isentropic circulation at high latitudes, while prescribed warming of the ocean surface increases PHT by strengthening the moist isentropic circulation. Inter-model spread of PHT into the Arctic reflects the tug-of-war between sea-ice and surface-warming effects.

58 GEOSCIENCES↗

An Edge Alignment-Based Orientation Selection Method for Neutron Tomography

Neutron computed tomography (nCT) is a 3D char-acterization technique used to image the internal morphology or chemical composition of samples in biology and materials sciences. A typical workflow involves placing the sample in the path of a neutron beam, acquiring projection data at a predefined set of orientations, and processing the resulting data using an analytic reconstruction algorithm. Typical nCT scans require hours to days to complete and are then processed using conventional filtered back-projection (FBP), which performs poorly with sparse views or noisy data. Hence, the main methods in order to reduce overall acquisition time are the use of an improved sampling strategy combined with the use of advanced reconstruction methods such as model-based iterative reconstruction (MBIR). In this paper, we propose an adaptive orientation selection method in which an MBIR reconstruction on previously-acquired measurements is used to define an objective function on orientations that balances a data-fitting term promoting edge alignment and a regularization term promoting orientation diversity. Using simulated and experimental data, we demonstrate that our method produces high-quality reconstructions using significantly fewer total measurements than the conventional approach.

Yang, Diyu↗

Deep Learning Based Frequency Stability Assessment in Power Grid with High Renewables

Frequency stability assessment is one critical aspect of power system security assessment. Traditional N-1 screening method is based on the simulations of a few typical daily and seasonal operation scenarios. However, the increasing integration of inverter-based renewables and the retirement of conventional synchronous generators result in decreasing system inertia and growing complexity of system operating conditions. Selecting a few typical operation scenarios cannot cover all operating conditions, and the time-domain simulation of all operation conditions requires tremendous time. This paper proposes a more efficient frequency stability assessment method based on deep learning. The affinity propagation clustering algorithm is used to divide the dataset into different clusters, so the selected dataset for training can cover the diversified operating conditions as much as possible. Also, feature normalization is applied to both the training dataset and testing dataset in order to remove any unnecessary bias. Especially, trained model based on full dataset normalization has bounded error in the prediction. The case study on the reduced 240-bus WECC system demonstrates that the proposed method can predict accurate frequency nadir with limited training dataset. The deep learning model using the revised feature normalization can predict more accurate frequency nadir than that using the traditional feature normalization and has very small maximum prediction error.

affinity propagation↗

DG2DAG: Learning Directed Acyclic Graphs from Functional Priors

Physics-based systems-of-systems models are computationally expensive. Reduced graphical models can decrease computational complexity, but may not proffer an end-to-end model from upstream inputs to downstream outputs. We consequently are interested in reducing models on directed graphs to models on a directed acyclic subgraph such that preserves accurate reconstruction of nodes. The consequence is a model with a topological ordering, providing a one-way flow of computation, and a causal interpr

Voronin, Alexey [Sandia National Laboratories (SNL↗

Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1

Abstract. In this paper we develop a novel framework aimed to significantly reduce biases related to marine stratocumulus clouds in general circulation models (GCMs) while circumventing excessive computational cost requirements. Our strategy is to increase the horizontal resolution using a regionally refined mesh (RRM) over our region of interest in addition to using the Framework for Improvement by Vertical Enhancement (FIVE) to increase the vertical resolution only for specific physical processes that are important for stratocumulus. We apply the RRM off the coast of Peru in the southeastern Pacific, a region that climatologically contains the most marine stratocumulus in the subtropics. We find that our new modeling framework is able to replicate the results of our high-resolution benchmark simulation with much fidelity, while reducing the computational cost by several orders of magnitude. In addition, this framework is able to greatly reduce the long-standing biases associated with marine stratocumulus in GCMs when compared to the standard-resolution control simulation.

54 ENVIRONMENTAL SCIENCES↗